To maintain a digital repository, digitizing of books is performed, and digitizing requires scanning of books. When the thick bound books are scanned to capture the twin-pages (both left and right pages of an open book), there are some unwanted defects, which may get introduced. These defects includes: (1) pyramid shaped darker region primarily caused at the center, where the surface of the book is not completely in contact with the scan-bed, (2) darker regions caused at the borders and corners of the book, where the page touching the scan-bed to the outer cover of the book forms a slope and also due to the gap introduced between the scan-bed and the scanner-cover plate, and (3) the orientation distortion introduced due to disproportionate distribution of the pages on either sides. If these defects remain uncorrected then a large amount lot of cartridge/toner ink is consumed when these scanned images are printed. Cartridge and toner ink are valuable resource for a printer and an efficient usage of the toner ink is a value add for any printer.
Presently, there exist a technique that attempts to classify the noises present in scanned images specifically related to horizontal line structures. Another existing technique identifies pixel locations with questionable colors in the scanned images. Another existing method eliminates border effect caused while scanning the document and cropping the book region. Yet another existing technique corrects the distortion caused along the spine of the book and warping of words in the shadow. Additional solutions correct uneven illumination and color cast problem. Other technique straightens out the text lines in scanned images and correct the perspective distortion of the characters at the binding edge or spine of the book. Moreover, other technique focuses on skew detection and correction based on a plurality of lines. Additional technique creates a uniform lighting for archival-quality but still document acquisition remains a non-trivial problem. The existing solutions solve the issues but the solutions only consider images that are free from skew and are gray scale. Also, none of the existing solutions focus on automatic correction of the defects caused while scanning the documents.
Hence, in light of the limitations with existing techniques, there arises a need for improved methods and systems for auto correction of defects in scanned images.